Open AccessPrediction of trust propensity from intrinsic brain morphology and functional connectome
Author(s) -
Feng Chunliang,
Zhu Zhiyuan,
Cui Zaixu,
Ushakov Vadim,
Dreher JeanClaude,
Luo Wenbo,
Gu Ruolei,
Wu Xia,
Krueger Frank
Publication year - 2021
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.25215
Subject(s) - connectome , distrust , psychology , neuropsychology , multivariate statistics , interpersonal communication , functional connectivity , cognitive psychology , computer science , neuroscience , social psychology , machine learning , cognition , psychotherapist
Trust forms the basis of virtually all interpersonal relationships. Although significant individual differences characterize trust, the driving neuropsychological signatures behind its heterogeneity remain obscure. Here, we applied a prediction framework in two independent samples of healthy participants to examine the relationship between trust propensity and multimodal brain measures. Our multivariate prediction analyses revealed that trust propensity was predicted by gray matter volume and node strength across multiple regions. The gray matter volume of identified regions further enabled the classification of individuals from an independent sample with the propensity to trust or distrust. Our modular and functional decoding analyses showed that the contributing regions were part of three large‐scale networks implicated in calculus‐based trust strategy, cost–benefit calculation, and trustworthiness inference. These findings do not only deepen our neuropsychological understanding of individual differences in trust propensity, but also provide potential biomarkers in predicting trust impairment in neuropsychiatric disorders.